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HIGHLIGHTS ARCHIVE
Division Highlights


A Nonreimbursable Space Act Agreement signed by NASA and US Airways
May 17, 2013

Photo of a NASA researcher as he points out something on the computer screen, which shows SARDA.
The Spot and Runway Departure Advisor (SARDA)

NASA and US Airways have signed a Nonreimbursable Space Act Agreement (NRSAA) to jointly build and test a prototype decision-support tool (DST) for ramp operators at the Charlotte Douglas International Airport (CLT) (Charlotte, North Carolina). The automation will assist ramp operators by providing an optimal push back schedule for departure aircraft in the presence of uncertainties, and thus, improve efficiency of traffic on the airport surface.

NASA has developed SARDA (Spot and Runway Departure Advisor), an innovative technology for optimal surface traffic sequencing. SARDA provides a collaborative DST for airline operators and tower controllers to enhance surface traffic efficiency by reducing delays in departure queues. The core components of the SARDA tool, consisting of the scheduling algorithm, taxi prediction algorithm, and interfaces with both the Air Traffic Control (ATC) and airline, have shown great promise in reducing ground traffic congestion through human-in-the-loop simulations. Under this Agreement, SARDA functions will be adapted to CLT operations, and NASA and US Airways will jointly develop a customized SARDA User Interface. If this development effort is successful, US Airways could benefit by saving direct operational costs through reduction of taxi delays and fuel usage. The airline may also gain better connection of passengers and baggage, with more predictable service times for departing flights. Benefits are also anticipated for the Federal Aviation Administration through enhanced efficiency and predictability of surface operations, which in turn is expected to improve the efficiency and predictability of the National Airspace System. (POC: Yoon Jung)



Scaled-Down Robot Model Data Collection and Analysis of Aircraft Ramp Area Maneuvers
May 17, 2013

Aircraft maneuvers inside the airport ramp area are frequently not confined to well-defined route segments and are subject to uncertainties due to the many different parties responsible for aircraft and gate operations. Detailed high-resolution data about aircraft maneuvers in the ramp area are not currently available. NASA is collaborating with the University of California, Santa Cruz (UCSC) to research the structure of surface traffic conflicts and their resolutions by using E-puck robots. The goal of this research is to develop a stochastic control theory-based algorithm for gate pushback control under the presence of arrival and departure uncertainties. The UCSC researchers have matched their robot kinematics to the kinematics of a B747-400. The human operator “pilot” drives the E-puck, which moves as if it were an aircraft. The maneuvers are recorded by a video camera. These records are used to compute time intervals and maneuver types for aircraft push-backs that provide maximum flexibility for ramp area operations meeting a specified ramp area exit schedule.

The data collected so far include arrival and departure trajectories modeled for the Dallas/Fort Worth International Airport (DFW) Terminal C ramp area, as well as selected departure trajectories for ramp areas of Charlotte Douglas International Airport (CLT). The analysis of the DFW data provides an insight into spatio-temporal conflicts among aircraft, as well as their structure with respect to aircraft push-back times. It is anticipated that the results will be integrated with the Spot and Runway Departure Advisor (SARDA) research to help the implementation to a specific airport ramp area, and which may someday be applied to a broader selection of airport ramp area layouts. (POC: Waqar Malik)

This image shows 3 aircraft icons parked at a semi-circle (open-side up) which is labeled C, B, and A from left to right underneath, which represent gates. A solid dot labeled Taxiway Spot in located in the bottom-right below the semi-circle and aircraft. Trajectory 1 for Aircraft A shows that the aircraft backs up in a curve shape to the right before proceeding to the taxiway spot. Trajectory 2 for Aircraft B shows that the aircraft backs up in a curve to the right before proceeding to the taxiway spot. Trajectory 3 for Aircraft B shows that the it can also back up in a curve to the right before proceedign to the taxiway spot. Trajectory 4 for Aircraft C shows that it backs up in a curve to the left before proceeding to the taxiway spot.
Fig.1 Ramp area scheduling problem: the aircraft are parked at gates A, B and C, and scheduled to be at the taxiway spot at a given time. Trajectories 1 and 4 represent trajectories of the aircraft parked at gates A and C, respectively; 2 and 3 represent the trajectories of the aircraft parked at gate B, which can push back to the right (BR), or to the left (BL), respectively.

This image shows a semi-circle (open-side up), four different sets of colored lines starting from points along the bottom of the semi-circle and leading to the bottom right corner of the image representing a taxiway spot, and a puck-like robot representing an aircraft. The first set of trajectories starts at the bottom-left of the semi-circle and shows that the robot backed up in a curve to the left before proceeding to the taxiway spot. The second set of trajectories sharts in the bottom center of the semi-circle and shows that the robot backed up in a curve to the left before proceeding to the taxiway spot. The third set of trajectories also begins at the center and shows that the robot backed up to the right before proceeding to the taxiway spot. The fourth set of trajectories begins at the bottom-right of the semi-circle and shows that the robot backed up in a curve to the right before proceeding to the taxiway spot.
Fig. 2 A fraction of experimentally recorded trajectories in a layout of the scaled-down ramp area and an E-puck robot



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